Light source color resolution evaluation method, device, equipment and storage medium

Abstract

The application discloses a light source color resolution evaluation method, device and equipment and a storage medium, and relates to the technical field of light source quality testing. The spectral power distribution of a test light source is acquired under multiple exit angles, and the bidirectional reflectance factor of a test color sample is combined to calculate three stimulus values and white point three stimulus values. The hue angle, brightness value and saturation value of each test color sample under the exit angle are calculated according to the three stimulus values and the white point three stimulus values. The comprehensive color error value of the test light source relative to a reference light source under the exit angle is obtained according to the aforementioned three parameters. The color resolution index of the test light source is obtained according to the neutral density index of the test light source and the comprehensive color error value corresponding to each exit angle. The spectral power distribution is collected under multiple exit angles, the color rendering performance of the light source in the front is considered, and the spectral output difference under different angles is also considered, so that the color rendering consistency and the directional characteristics of the light source in the spatial distribution can be comprehensively reflected.

Description

Technical Field

[0001] This invention relates to the field of light source quality testing technology, and in particular to a method, apparatus, device, and storage medium for evaluating the color resolution of a light source. Background Technology

[0002] With the rapid development of semiconductor lighting technology and the widespread adoption of human-centered lighting concepts, the color rendering quality of light source products has become one of the core indicators for measuring their quality. Whether it's specialized lighting equipment or displays for electronic devices, consumers are placing increasingly higher demands on the visual effects of light source products, expecting a more realistic, natural, and comfortable lighting experience. Color resolution is one of the key indicators for measuring the color rendering quality of light source equipment. Color resolution reflects the ability of a light source to distinguish and present subtle color differences when illuminating an object. Light sources with high color resolution can more clearly display the layers and details of object colors, thus providing a richer and more realistic visual experience.

[0003] In the existing technology, the group standard T / CIES036-2025 discloses a color resolution index system consisting of the absolute color resolution index (CDM), the color resolution complement index (CDMe), and the relative color resolution index (CDMr). Among them, CDM is calculated based on the light source error score and neutrality and is used to characterize the color resolution under cross-color temperature conditions. CDMe introduces illuminance correction on the basis of CDM to better reflect the resolution performance under different illuminance conditions. CDMr obtains the relative resolution index under the same color temperature conditions by comparing the CDM of the tested light source with that of the reference light source, thereby realizing a comprehensive evaluation under cross-color temperature, different illuminance, and same color temperature scenarios.

[0004] However, for light sources with different directional distributions, the evaluation of their angle-dependent color resolution may not be accurately reflected. Summary of the Invention

[0005] In view of this, the present invention provides a method, apparatus, device and storage medium for evaluating the color resolution of a light source, in order to solve the problem that the prior art cannot truly reflect the color resolution evaluation related to its angle.

[0006] The technical solution adopted in this invention is:

[0007] In a first aspect, the present invention provides a method for evaluating the color resolution of a light source, the method comprising:

[0008] Based on the output power of the test light source, obtain the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles;

[0009] For each exit angle, based on the bidirectional reflectance factor of multiple test color samples at the exit angle, calculate the tristimulus value and white point tristimulus value of each test color sample at the exit angle of the test light source;

[0010] Based on the tristimulus values ​​and white point tristimulus values ​​of each test color sample at the specified exit angle, calculate the hue angle, lightness value, and saturation value of each test color sample at the specified exit angle.

[0011] Based on the hue angle, lightness value, and saturation value of each test color sample at the emission angle, the comprehensive color error value of the test light source relative to the reference light source at the emission angle is obtained.

[0012] The color resolution index of the test light source is obtained based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle.

[0013] Preferably, the step of calculating the tristimulus value and white point tristimulus value of each test color sample at the emission angle of the test light source, based on the bidirectional reflectance factor of multiple test color samples at the emission angle, for each emission angle, includes:

[0014] For each emission angle, the bidirectional reflectance factor of multiple test color samples was obtained;

[0015] Based on the CIE color matching function, the bidirectional reflectance factor, the preset wavelength range, and the spectral power distribution, calculate the tristimulus values ​​of each test color sample under the test light source;

[0016] Based on the CIE color matching function, the preset wavelength range, and the spectral power distribution, the white point tristimulus value of the light source under the test light source is calculated.

[0017] Preferably, the step of calculating the hue angle, lightness value, and saturation value of each test color sample at the emission angle based on the tristimulus value and white point tristimulus value of each test color sample at the emission angle includes:

[0018] For each test color sample, the input pairing required for color adaptation conversion is performed based on the tristimulus value of the test color sample and the corresponding white point tristimulus value, resulting in the input pair for color adaptation conversion;

[0019] The cone response value is obtained by color adaptation conversion of the tristimulus values ​​of the test color sample based on the white point tristimulus values.

[0020] Based on the environment or observation settings, the visual cone response value is subjected to brightness adaptation conversion and nonlinear response compression processing to obtain the visual cone reference value;

[0021] Calculate the first color channel value and the second color channel value based on the aforementioned cone reference value;

[0022] Calculate the hue angle based on the first color channel value and the second color channel value;

[0023] The luminance channel value corresponding to the aforementioned cone reference value is used as the luminance value;

[0024] The saturation value is calculated based on the Euclidean modulus of the first and second color channel values.

[0025] Preferably, obtaining the comprehensive color error value of the test light source relative to the reference light source at the emission angle based on the hue angle, lightness value, and saturation value of each test color sample at the emission angle includes:

[0026] The multiple test color samples are classified according to their color attributes to form multiple color sample groups;

[0027] For each color sample group, calculate the error values ​​relative to the reference light source in each dimension of hue angle, lightness value and saturation value of the test color sample in the color sample group at the emission angle.

[0028] Based on the sensitivity of the human eye to changes in different color attributes, corresponding perceptual weighting factors are assigned to the error values ​​of each dimension under the given emission angle.

[0029] The error values ​​of each dimension of the test color sample in the color sample group at the emission angle are weighted and combined with their perception weighting factors to obtain the initial color error value of the test color sample in the color sample group at the emission angle.

[0030] The initial color error values ​​of the test color samples in each color sample group at the emission angle are statistically processed to calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle.

[0031] Preferably, the statistical processing of the initial color error values ​​of the test color samples in each color sample group at the emission angle to calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle includes:

[0032] Based on the initial color error value of the test color sample of each color sample group at the emission angle, an aggregation operation is performed to obtain the group color error value of each color sample group at the emission angle.

[0033] Based on the differences in importance of different color attribute groups in visual tasks, a grouping weight factor is assigned to the grouping color error value of each color sample group.

[0034] Based on the group color error value and group weight factor of each color sample group, the comprehensive color error value of the test light source relative to the reference light source at the emission angle is calculated.

[0035] Preferably, the method further includes:

[0036] Based on the color temperature parameters of the test light source, an associated reference light source is obtained, and the reference spectral power distribution of the reference light source within the preset wavelength range is calculated.

[0037] The reference color resolution index of the reference light source is calculated based on the reference spectral power distribution and multiple test color samples;

[0038] The relative color resolution index of the test light source is calculated based on the reference color resolution index and the color resolution index.

[0039] Preferably, obtaining the associated reference light source based on the color temperature parameters of the test light source includes:

[0040] If the color temperature parameter is less than the first color temperature threshold, the obtained reference light source is a Planck illuminator;

[0041] If the color temperature parameter is greater than the second color temperature threshold, the obtained reference light source is a daylight illuminator; wherein, the second color temperature threshold is greater than the first color temperature threshold;

[0042] If the color temperature parameter is between the first color temperature threshold and the second color temperature threshold, the obtained reference light source is a mixture of the Planck illuminator and the daylight illuminator.

[0043] Secondly, the present invention provides a light source color resolution evaluation device, the device comprising:

[0044] The acquisition module is used to acquire the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles;

[0045] The tristimulus value module is used to calculate the tristimulus value and white point tristimulus value of each test color sample at the emission angle of the test light source, based on the bidirectional reflectance factor of multiple test color samples at the emission angle.

[0046] The calculation module is used to calculate the hue angle, lightness value and saturation value of each test color sample at the emission angle based on the tristimulus value and white point tristimulus value of each test color sample at the emission angle.

[0047] The error value module is used to obtain the comprehensive color error value of the test light source relative to the reference light source at the emission angle based on the hue angle, lightness value and saturation value of each test color sample at the emission angle.

[0048] The color resolution module is used to obtain the color resolution index of the test light source based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle.

[0049] Thirdly, embodiments of the present invention also provide an electronic device, including: at least one processor, at least one memory, and computer program instructions stored in the memory, which, when executed by the processor, implement the method of the first aspect described above.

[0050] Fourthly, embodiments of the present invention also provide a storage medium storing computer program instructions thereon, which, when executed by a processor, implement the method of the first aspect described above.

[0051] In summary, the beneficial effects of the present invention are as follows:

[0052] The present invention provides a method, apparatus, device, and storage medium for evaluating the color resolution of a light source. Based on the output power of the test light source, the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles is obtained. For each emission angle, based on the bidirectional reflectance factor of multiple test color samples at that emission angle, the tristimulus values ​​and white point tristimulus values ​​of each test color sample at that emission angle are calculated. Based on the tristimulus values ​​and white point tristimulus values ​​of each test color sample at that emission angle, the hue angle, lightness value, and saturation value of each test color sample at that emission angle are calculated. Based on the hue angle, lightness value, and saturation value of each test color sample at that emission angle, the comprehensive color error value of the test light source relative to a reference light source at that emission angle is obtained. Based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle, the color resolution index of the test light source is obtained. This invention collects spectral power distribution at multiple emission angles, taking into account not only the color rendering performance of the light source directly in front of it, but also the differences in spectral output at different angles, thereby comprehensively reflecting the color rendering consistency and directional characteristics of the light source in spatial distribution. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, and these are all within the protection scope of the present invention.

[0054] Figure 1 This is a flowchart illustrating the light source color resolution evaluation method in Embodiment 1 of the present invention. Figure 1 ;

[0055] Figure 2 This is a flowchart illustrating the light source color resolution evaluation method in Embodiment 1 of the present invention. Figure 2 ;

[0056] Figure 3 This is a flowchart illustrating the light source color resolution evaluation method in Embodiment 1 of the present invention. Figure 3 ;

[0057] Figure 4 This is a flowchart illustrating the light source color resolution evaluation method in Embodiment 1 of the present invention. Figure 4 ;

[0058] Figure 5 This is a flowchart illustrating the light source color resolution evaluation method in Embodiment 1 of the present invention. Figure 5 ;

[0059] Figure 6 This is a structural block diagram of the light source color resolution evaluation device in Embodiment 2 of the present invention;

[0060] Figure 7 This is a schematic diagram of the electronic device in Embodiment 3 of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. In the description of the present invention, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, the element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Where there is no conflict, embodiments of the present invention and the various features thereof can be combined with each other, all of which are within the scope of protection of the present invention.

[0062] Example 1

[0063] Please see Figure 1 , Figure 1 This is an optional flowchart of the light source color resolution evaluation method provided in the embodiments of the present invention. Figure 1 The method described may include, but is not limited to, steps S1 to S1. It is also understood that this embodiment... Figure 1 The order of steps S1 to S1 is not specifically limited. The order of steps can be adjusted or some steps can be reduced or added according to actual needs.

[0064] S1. Based on the output power of the test light source, obtain the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles;

[0065] Specifically, the test light source is first subjected to spectral measurement or simulation to obtain its spectral power distribution (SPD) at different emission angles. The preset wavelength range can be set to 380nm to 780nm, and a sufficiently fine sampling interval is set for spectral sampling, such as 5nm or 10nm, to ensure comprehensive accuracy in the calculation process. When the SPD data of the test light source is missing within the preset wavelength range, for example, if the data only covers 400nm to 700nm, the SPD values ​​corresponding to the missing wavelength range are filled with zero. This ensures that subsequent calculations can be performed within the preset wavelength range, avoiding calculation deviations due to incomplete data. It is understood that the preset wavelength range can be set by those skilled in the art according to actual conditions, and this embodiment does not impose any limitations on this. Unlike traditional spectral measurements that only measure the spectrum in a single direction, this step collects data from multiple angles, reflecting the spatial distribution characteristics of the light source. By acquiring spectral information from multiple angles, the problem of missing directional differences in the light source when using only a single angle can be avoided. The benefit of this step is that it enables the establishment of the spectral distribution of the test light source in the angular domain, providing a more realistic data basis for subsequent colorimetric calculations.

[0066] In some embodiments, S1, obtaining the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles based on the output power of the test light source, includes:

[0067] When the output power is greater than or equal to the output power threshold, the incident irradiance reaching the detector is calculated based on the output power.

[0068] Specifically, the output power threshold is a set boundary used to distinguish between high and low light source intensity. When the output power is greater than or equal to the threshold, the light source is considered a high-power source, and special attention needs to be paid to whether the detector will saturate due to the strong signal. Incident irradiance refers to the radiant power density (light energy received per unit area) of the light source reaching the detector surface under specific geometric conditions; it directly determines the strength of the detector signal. When the light source output power is greater than or equal to the set threshold, the rated power of the light source is first converted into the incident irradiance reaching the detector surface by combining the emission angle distribution, ranging, and receiving aperture, etc. This is done to convert the overall energy level of the light source into a quantity relevant to the detector's reception, facilitating subsequent matching with detector performance. Its beneficial effect is that the light intensity that the detector may receive can be estimated before actual measurement, thereby identifying potential measurement risks in advance.

[0069] The incident irradiance is compared with the linear operating range of the detector to determine whether there is a risk of detector saturation.

[0070] Specifically, the linear operating range of a detector refers to the range within which the detector maintains a linear relationship between the output signal and the incident light intensity. Exceeding this range will cause saturation, leading to measurement distortion. Saturation risk refers to the possibility that the detector will exceed its linear region when the incident light is too strong, manifesting as the output signal reaching its maximum or the spectral shape being clipped. The calculated signal amplitude corresponding to the incident irradiance is compared with the detector's linear operating range, and a safety margin is set (e.g., not exceeding 80% of full scale). This allows determination of whether the light source, under the current settings, will cause the detector to enter the saturation region. Its beneficial effect is that through quantitative judgment, direct signal distortion during acquisition is avoided, improving the reliability and controllability of the measurement.

[0071] If there is a risk of detector saturation, the parameters are adjusted until the judgment result indicates that there is no risk of detector saturation.

[0072] Specifically, when the comparison results indicate a risk of saturation, the acquisition parameters are gradually adjusted, such as shortening the integration time, reducing the detector gain, inserting a neutral density filter, or increasing the ranging distance. After each adjustment, a new prediction is made until it is confirmed that the detector is operating within the safe linear region. The logic behind this is to control the signal within a suitable range by reducing the light flux received by the detector or reducing its response amplification. The beneficial effect is to ensure that the detector output remains linear, avoiding data corruption due to overexposure.

[0073] Furthermore, if there is a risk of detector saturation, parameters are adjusted until the determination result indicates that there is no risk of detector saturation, including:

[0074] If there is a risk of detector saturation, obtain the parameter adjustment methods, which include:

[0075] The integration time collected by the detector is gradually reduced according to a preset ratio;

[0076] And / or, gradually reduce the gain acquired by the detector according to a preset gain level;

[0077] And / or, a neutral density filter is inserted in the optical path before the receiving end of the detector;

[0078] And / or, if a neutral density filter is already present, increase the neutral density level of the neutral density filter;

[0079] Reassess whether there is a risk of detector saturation.

[0080] If the judgment result indicates that there is a risk of detector saturation, then adjust the parameters according to the aforementioned adjustment method until the judgment result indicates that there is no risk of detector saturation.

[0081] Specifically, integration time refers to the length of time the detector accumulates the optical signal during a single spectral acquisition. In the previous step, when a saturation risk is detected after calculating the incident irradiance and comparing it with the detector's linear range, shortening the integration time can directly reduce the number of photons per unit acquisition cycle, thereby reducing the detector's output intensity. Gain is the electronic amplification factor of the detector when converting the optical signal into a digital signal. When shortening the integration time is still insufficient to avoid saturation, lowering the gain can reduce the amplification ratio of each photoelectron in the digital domain, causing the output signal to move away from full scale and avoiding digital overshoot. A neutral density filter is an optical element that can uniformly attenuate light intensity across the entire wavelength range. After being inserted into the optical path, it can reduce the overall light flux incident on the detector without changing the shape of the spectral power distribution. Neutral density filters have different attenuation grades (such as ND0.3, ND0.6, ND1.0), with higher values ​​indicating stronger attenuation. When a saturation risk is still detected after inserting a single ND filter, a higher-grade ND filter can be replaced or stacked to further attenuate the incident light. When a detector saturation risk is detected, feasible parameter adjustment methods are first obtained, including gradually attenuating the integration time according to a preset ratio, gradually reducing the gain according to a preset gain level, inserting a neutral density filter in the optical path, or increasing the neutral density level, etc., and applied sequentially according to a predetermined priority. Among them, shortening the integration time is given priority to directly reduce the photon accumulation, followed by reducing the signal amplification factor by reducing the gain. If necessary, optical attenuation methods are used to weaken the incident flux as a whole. Immediately after each adjustment, a pre-scan is performed to re-evaluate the signal. The acquired signal is compared with the detector's linear operating range to check whether the peak value falls within the safe zone and to confirm that there is no clipping or top-level output. If a saturation risk still exists, the above adjustment steps are continued until the re-evaluation result shows that the signal is within the linear operating range. This ensures that the detector output data is not saturated and maintains true linear characteristics, thereby providing reliable input for subsequent tristimulus value and colorimetric evaluation calculations.

[0082] Obtain the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles.

[0083] After confirming the absence of saturation risk, the light source's spectrum is collected at multiple emission angles, covering a preset wavelength range (e.g., 380–780 nm), and the data undergoes dark field subtraction and formatting. The resulting spectral power distribution can serve as the basis for subsequent tristimulus values ​​and visual feature calculations. Its advantages include obtaining accurate, linear, and comparable multi-angle spectral data even under high power conditions, ensuring the accuracy of subsequent color rendering and resolution evaluations.

[0084] In some embodiments, S1, obtaining the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles based on the output power of the test light source, includes:

[0085] When the output power is less than the output power threshold, a pre-scan is performed based on the output power and the detector noise characteristics to obtain an initial set of noise parameters;

[0086] Specifically, pre-scanning refers to performing one or a small number of measurements using fixed and relatively safe acquisition parameters (short integration time, reference gain) to assess signal strength and noise levels. The initial noise parameter set refers to the set of parameters obtained by decomposing and quantifying various types of noise (readout noise, dark current noise, photon shot noise, etc.) using pre-scan data. This step involves performing one to several measurements with a fixed, short integration time and reference gain, while simultaneously acquiring dark field / background frames. The average and variance of each wavelength point are statistically analyzed, and combined with the detector datasheet parameters (dark current, nominal readout noise values), the magnitude and proportion of readout noise, dark current noise, and photon shot noise are fitted or estimated to form the initial noise parameter set. This is done because signals are weak at low power, and the relative contributions of different noise sources vary greatly; quantifying the noise composition first allows for determining whether subsequent adjustments to parameters such as gain are necessary. The beneficial effects are: understanding the noise landscape with a small amount of data, avoiding blind parameter tuning, shortening subsequent convergence time, and reducing the risk of acquisition failure.

[0087] The dominant noise is determined based on the initial set of noise parameters;

[0088] Specifically, dominant noise refers to the type of noise that has the greatest impact on the signal-to-noise ratio (SNR) and accounts for the largest proportion under the current acquisition conditions. This step determines the dominant noise type by converting each noise component (readout, dark current, photon shot) to the same dimension as the current signal (such as DN or electron number) and comparing their root mean square (RMS) magnitude or weighted contribution in the visible light band. The purpose is that dominant noise determines the most effective direction for improving SNR. If readout noise is dominant, the signal should be improved in the digital domain first; if photon noise is dominant, increasing the gain is not very meaningful. The beneficial effect is to clearly identify the root cause and avoid ineffective or side-effect-prone parameter tuning.

[0089] If the dominant noise is readout noise, then gain adjustment is performed to obtain the adjusted gain;

[0090] Specifically, readout noise refers to fixed noise (such as amplifier noise and quantization noise) generated by the detector / ADC electronic link that is independent of the photon count. Gain is the scaling factor that amplifies the charge / voltage signal to a digital count (DN); the higher the gain, the easier it is for weak signals to be boosted in the digital domain, but saturation occurs earlier. This step increases the gain to a range that is significantly higher than the readout noise floor without triggering saturation, without changing the integration time and optical path. For example, a peak target of ≈ (0.3–0.6)FS is set, and the average signal is required to be ≥ k × readout noise RMS (e.g., k = 8~10). Since readout noise is independent of the photon count, increasing the gain can amplify the ratio of the useful signal to the readout noise, thereby improving the resolution and SNR in the digital domain.

[0091] The beneficial effect is that it significantly improves the measurability of weak signals without changing the incident light amount, while maintaining sufficient full-scale margin and reducing the risk of saturation.

[0092] Based on the adjusted gain, the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles is obtained.

[0093] Specifically, by locking the gain setting, spectral power distributions are sequentially acquired at multiple emission angles. Under low power conditions, stable gain and noise suppression strategies are key to obtaining reliable spectral power distributions. The angle sequence ensures that subsequent colorimetric evaluation has spatial distribution information. The beneficial effect is that it obtains multi-angle spectral power distributions with sufficient SNR and linear reliability even under weak signal conditions, which can be directly used for accurate calculation of tristimulus values ​​and white point, reducing error propagation.

[0094] S2. For each exit angle, based on the bidirectional reflectance factor of multiple test color samples at the exit angle, calculate the tristimulus value and white point tristimulus value of each test color sample at the exit angle of the test light source.

[0095] Specifically, Test-Colour Samples (TCS) are a set of standard color samples used in fields such as color science, textiles, coatings, and plastics to test and calibrate color measurement instruments, evaluate color quality, or perform color matching. These color samples typically possess known and stable color characteristics and can serve as reference standards to ensure the consistency and accuracy of color measurements. In this embodiment, 85 samples are calculated. R d Tristimulus values ​​of the test color samples under the test light source, 85 R d Test color samples are a set of standard color samples used to evaluate the color rendering performance of a light source. These color samples cover the range of colors commonly found under natural and artificial light sources and can comprehensively reflect the ability of a light source to reproduce the colors of objects.

[0096] Tristimulus values ​​are an important concept in color science, used to quantify color. They represent the degree of stimulation from the three primary colors that cause the human retina to perceive a particular color. In the CIE (International Commission on Illumination) XYZ color space, tristimulus values ​​are represented by X, Y, and Z, corresponding to the stimulation levels of the three primary colors: red, green, and blue, respectively. Tristimulus values ​​can be calculated from the spectral power distribution to represent the color perception attributes of the test color sample under the test light source, and reference tristimulus values ​​can be calculated for each test color sample based on the reference spectral power distribution.

[0097] At each exit angle, the bidirectional reflectance factor (BRF) of multiple test color samples is obtained. This factor describes the reflectance characteristics of the test color samples under different incident and exit angles. The BRF is then combined with the spectral power distribution at that angle and integrated using the CIE colorimetric matching function to obtain the tristimulus values ​​for each test color sample, as well as the tristimulus value for the reference white point. This approach considers not only the angular distribution of the light source but also the directional reflectance effect of the color sample material. The advantage of this step is that it makes the tristimulus value calculation closer to real observation conditions, avoiding the neglect of reflectance differences in high-gloss or directionally sensitive color samples.

[0098] S3. Calculate the hue angle, lightness value, and saturation value of each test color sample at the specified emission angle based on the tristimulus value and white point tristimulus value of each test color sample at the specified emission angle.

[0099] Specifically, the hue angle is a parameter used to describe the position of a color on the color wheel. In a uniform color space, the hue angle is the angle between the position of a color stimulus and the positive axis (usually a reference axis, such as the red axis or an axis at a specific angle). This angle value can intuitively reflect the hue characteristics of a color and is an important way to distinguish and describe different colors in color science.

[0100] Brightness is a visual attribute that represents the lightness or darkness of a color. In the CIE system, it is commonly represented by L* (CIELAB) or J (CAM16, etc.), with values ​​ranging from 0 to 100, where 0 represents black and 100 represents ideal white. It is mainly determined by the intensity of light stimulation, that is, the amount of light entering the human eye.

[0101] Saturation is an attribute that represents the vividness or purity of a color. Mathematically, it is often expressed through the Euclidean modulus of color channels a and b. To calculate. High saturation makes colors appear vibrant and pure; low saturation makes colors appear dull or whitish.

[0102] First, the tristimulus values ​​of the test color sample and the white point tristimulus values ​​are subjected to color adaptation conversion to obtain the white point-corrected cone response values. Then, depending on the environment or observation conditions, the cone response values ​​are subjected to brightness adaptation or nonlinear compression to obtain a cone reference value that better matches visual perception. Next, the first and second color channels are calculated from the reference values, and the hue angle is obtained through arctangent calculation. Simultaneously, the brightness channel is used as the lightness value, and the saturation value is obtained using the Euclidean modulus of the two color channels. The beneficial effect of this step is that, by simulating the human eye's visual processing mechanism, physical spectral data is transformed into perceptual characteristics such as hue angle, lightness, and saturation, better reflecting the observer's actual visual experience.

[0103] S4. Based on the hue angle, lightness value, and saturation value of each test color sample at the emission angle, obtain the comprehensive color error value of the test light source relative to the reference light source at the emission angle;

[0104] Specifically, the comprehensive color error value is used to measure the difference between the color presented by the test light source and the standard or expected color. The hue angle, lightness, and saturation of each test color sample are compared with those under the reference light source, and the three-dimensional difference value is calculated. Then, based on the sensitivity of the human eye to changes in hue, lightness, and saturation, the difference values ​​of each dimension are weighted and combined to obtain the initial error value of each test color sample at that angle. Further, through color attribute grouping and statistical aggregation, the comprehensive color error value of the test light source at that emission angle is obtained. The beneficial effect of this step is that it not only captures the color difference of a single sample but also reflects the overall color rendering deviation of different categories of colors under angular conditions, which is more consistent with the subjective color rendering evaluation of the human eye.

[0105] S5. Based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle, obtain the color resolution index of the test light source.

[0106] Specifically, the neutrality index of the test light source is first calculated to measure whether its spectral distribution is biased towards a specific hue. Then, this neutrality index is fused with the comprehensive color error value at each emission angle, and a comprehensive index is obtained through a weighted or function mapping method. The final output color resolution index can simultaneously consider the angular consistency of the light source, color rendering accuracy, and overall neutral color performance. The advantage of this step is that it provides a more comprehensive evaluation standard than traditional color rendering indices, accurately characterizing the color rendering and resolution capabilities of the light source under multi-angle and multi-material conditions.

[0107] In some of the methods described, the neutrality index of the test light source is obtained as follows:

[0108] Calculate the color space coordinates of the test light source based on the tristimulus values ​​of the test light source;

[0109] Specifically, the tristimulus values ​​are calculated based on the spectral power distribution; color space coordinates are numerical representations used to quantify the physical properties of color in a specific color space. Taking the CIE 1976 u'v' color space as an example, it provides a two-dimensional coordinate system (u', v') to describe characteristics such as hue and saturation of colors. In this embodiment, the color space coordinates of the test light source in the CIE 1976 u'v' color space are calculated based on the tristimulus values. In this color space, each color can be represented as a point, and the coordinates of this point are the color space coordinates of that color.

[0110] The neutrality index of a light source is calculated based on color space coordinates.

[0111] The neutrality index of a test light source is calculated using color space coordinates. The neutrality index describes the degree of neutrality of the light source's color characteristics, i.e., whether the light source's color is close to a neutral color (such as white or gray). Neutral colors are generally considered to be colors without any color bias; they are located at the center of the color wheel and do not lean towards any particular hue. In the field of lighting, neutral light sources (or natural light sources) typically have color characteristics close to sunlight, are visually comfortable, and are suitable for various lighting scenarios.

[0112] In some implementations, such as Figure 2 As shown, S2, for each emission angle, based on the bidirectional reflectance factor of multiple test color samples at the emission angle, calculate the tristimulus value and white point tristimulus value of each test color sample at the emission angle of the test light source, including:

[0113] S21. For each emission angle, obtain the bidirectional reflectance factor of multiple test color samples;

[0114] Specifically, at each exit angle, the reflectance characteristics of multiple preset test color samples are measured or a database is accessed to obtain their bidirectional reflectance factor (BRF). The BRF characterizes the reflectance efficiency of the test color sample under specific incident and exit angles. Compared to the spectral reflectance factor at a fixed angle, it can more accurately describe the direction dependence of high-gloss, metallic, or textured materials. The beneficial effect of this step is that it provides angle-dependent input for subsequent tristimulus value calculations, enabling the results to reflect the true color rendering performance of the test color samples at different angles.

[0115] S22. Calculate the tristimulus values ​​of each test color sample under the test light source based on the CIE color matching function, the bidirectional reflectance factor, the preset wavelength range, and the spectral power distribution.

[0116] Specifically, the spectral power distribution of the test light source at that emission angle is multiplied by the BRF of the test color sample to obtain the effective reflectance spectrum of the color sample at that angle. This reflectance spectrum is then integrated with the CIE colorimetric matching function to obtain the three tristimulus values ​​(X, Y, and Z). The CIE colorimetric matching function is a standard function developed by the International Commission on Illumination (ICI) to simulate the weighted response of the human eye to the spectrum in three colors. The beneficial effect of this step is that it converts the physical spectral signal into a numerical representation relevant to human eye perception, allowing subsequent calculations to directly correspond to human color perception.

[0117] S23. Calculate the white point tristimulus value of the light source under the test light source based on the CIE color matching function, the preset wavelength range, and the spectral power distribution.

[0118] Specifically, the spectral power distribution of the test light source at that emission angle is weighted and integrated, without considering the BRF of the color sample, to obtain the white point tristimulus values ​​(Xw, Yw, Zw) of the light source at that angle. The white point represents the chromaticity coordinates of the light source itself and serves as the benchmark for subsequent color adaptation and color space conversion. The beneficial effect of this step is that it establishes a reference white point at each angle, which can offset the influence of differences in the color temperature of the light source during color adaptation, ensuring a uniform standard for color comparison at different angles.

[0119] In some implementations, such as Figure 3 As shown, S3, based on the tristimulus values ​​and white point tristimulus values ​​of each test color sample at the stated emission angle, calculate the hue angle, lightness value, and saturation value of each test color sample at the stated emission angle, including:

[0120] S31. For each test color sample, pair the inputs required for color adaptation conversion according to the tristimulus values ​​of the test color sample and the corresponding white point tristimulus values ​​to obtain the input pairs for color adaptation conversion.

[0121] Specifically, the tristimulus values ​​of each test color sample at the emission angle are paired with the white point tristimulus values ​​at the same angle, serving as inputs for color adaptation conversion. Color adaptation conversion is a crucial step in color science, used to eliminate the influence of differences in light source color temperature or white point. By establishing input pairs, it is ensured that the color calculation for each test color sample is referenced to the same white point. The beneficial effect of this step is that it provides a consistent benchmark for subsequent color adaptation, improving the accuracy of color comparisons under different light sources or angles.

[0122] S32. Based on the white point tristimulus value, perform color adaptation conversion on the tristimulus value of the test color sample to obtain the cone response value;

[0123] Specifically, a standard color adaptation tool (such as Bradford or CAT02) is first selected, and the tristimulus values ​​of the white point of the test light source are used as the "source white point," while the observer's reference white point (e.g., D65 or CIE standard light source white point) is used as the "target white point." For each test color sample, the system inputs the tristimulus values ​​obtained under the test light source into the color adaptation tool and transforms them to the cone cell response space corresponding to the target white point through matrix multiplication or linear transformation. After the transformation, three types of cone cell response values ​​are obtained, referred to here as cone response values. This simulates the adaptive process of the human eye under different light sources. The beneficial effect of this step is that it transforms physical measurement data into signals more consistent with human eye perception, making the calculation results closer to the real visual experience.

[0124] S33. Based on the environment or observation settings, the visual cone response value is subjected to brightness adaptation conversion and nonlinear response compression processing to obtain the visual cone reference value.

[0125] Specifically, simply performing color adaptation conversion is insufficient to fully simulate the human eye's visual response under varying light intensities. The human eye's photopic vision system possesses adaptive brightness capabilities, meaning it automatically adjusts its overall sensitivity as light intensity changes. Therefore, the obtained cone response values ​​require further brightness adaptation processing. Common methods, depending on complexity, include simple logarithmic compression of the Stevens power law or higher-order CIECAM brightness level mapping. This step non-linearly adjusts the original cone response according to overall brightness, compressing high-brightness bits and boosting low-brightness bits to obtain a more suitable cone reference value for color calculation. The beneficial effect of this step is to avoid calculation distortion caused by an excessively large brightness range, making changes in brightness more consistent with the subjective perception of the human eye.

[0126] S34. Calculate the first color channel value and the second color channel value based on the aforementioned cone reference value;

[0127] Specifically, the visual cone reference value is used to perform hand color calculations, converting it into first and second color channels (e.g., a and b channels). This channelization process can separate the directional information of the color. The beneficial effect of this step is that it simplifies the complex visual signal into two core dimensions, facilitating subsequent calculations of hue angle and saturation.

[0128] S35. Calculate the hue angle based on the first color channel value and the second color channel value;

[0129] Specifically, the angle of color on the two-dimensional channel plane is calculated using the arctangent function atan2(b,a) and mapped to the 0–360° range. The beneficial effect of this step is to obtain a color category index consistent with human subjective perception, used to distinguish the directions of colors such as red, green, and blue.

[0130] S36. Use the luminance channel value corresponding to the cone reference value as the luminance value;

[0131] Specifically, the luminance component of the cone reference value is directly taken as the lightness value, reflecting the luminance level of the test color sample at that angle. The beneficial effect of this step is that it preserves the human eye's intuitive perception of brightness and darkness, providing a key indicator for subsequent color rendering evaluation.

[0132] S37. Calculate the saturation value based on the Euclidean modulus of the first and second color channel values.

[0133] Specifically, the sum of the squares of the two color channel values ​​is taken as the square root to obtain the vector length of the color in the channel plane, i.e., saturation. The higher the saturation, the purer and more vivid the color. The beneficial effect of this step is that it quantifies the intensity of color, allowing the differences in color rendering under different light sources to be accurately represented.

[0134] In some implementations, such as Figure 4 As shown, S4, based on the hue angle, lightness value, and saturation value of each test color sample at the emission angle, obtain the comprehensive color error value of the test light source relative to the reference light source at the emission angle, including:

[0135] S41. Classify the multiple test color samples according to their color attributes to form multiple color sample groups;

[0136] Specifically, multiple pre-set test color samples are divided according to their color attributes (e.g., red, green, blue, or high saturation, low saturation, skin tone related groups, etc.), forming corresponding color sample groups. This grouping of color samples with similar properties facilitates subsequent intra-group statistics and inter-group comparisons. The advantage of this step is that it avoids a one-size-fits-all approach to all color samples, more closely reflects the differences in human perception of different color categories, and makes subsequent error analysis more scientific and reasonable.

[0137] S42. For each color sample group, calculate the error values ​​relative to the reference light source in each dimension of the hue angle, lightness value and saturation value of the test color sample in the color sample group at the emission angle.

[0138] Specifically, for each test color sample within a group, its hue angle, lightness value, and saturation value under the test light source are compared one by one with the corresponding values ​​under the same conditions under a reference light source, obtaining the difference values ​​in these three dimensions. This quantifies the specific deviations of the light source under different color groups and different angles. The beneficial effect of this step is that it breaks down perceptually relevant differences into three dimensions: hue, lightness, and saturation, making the evaluation indicators more detailed and able to capture specific sources of deviation that traditional ΔE evaluation cannot distinguish.

[0139] S43. Based on the sensitivity of the human eye to changes in different color attributes, assign corresponding perceptual weight factors to the error values ​​of each dimension under the emission angle.

[0140] Specifically, for the three dimensions of hue, lightness, and saturation, different weights are assigned to each dimension based on the human eye sensitivity curve from visual science research. For example, the human eye is more sensitive to changes in hue, followed by lightness, and relatively less sensitive to changes in saturation. This differentiated weighting makes the error calculation more consistent with the subjective perception of the human eye. The beneficial effect of this step is that it avoids simply treating the errors of each dimension as equal, thus making the final calculated deviation index more reflective of actual visual experience.

[0141] S44. The error values ​​of each dimension of the test color sample in the color sample group under the emission angle are weighted and combined with their perception weighting factors to obtain the initial color error value of the test color sample in the color sample group under the emission angle.

[0142] Specifically, the error values ​​of each test color sample in the dimensions of hue, lightness, and saturation are multiplied by their corresponding weighting factors, and the weighted results are then synthesized to obtain the initial color error value of the test color sample at that angle. In this way, the error of each sample considers not only its numerical magnitude but also its perceptual sensitivity. The beneficial effect of this step is that it transforms multidimensional errors into a single comprehensive index, simplifying subsequent grouping statistics while ensuring the consistency of this index with human visual perception.

[0143] S45. Statistically process the initial color error values ​​of the test color samples in each color sample group at the emission angle, and calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle.

[0144] Specifically, for all test color samples within each color sample group, their initial color error values ​​are statistically aggregated, for example, using methods such as mean, median, or weighted distribution, to obtain a representative error index for that group. Then, all color sample groups are combined as a whole to obtain the comprehensive color error value at that emission angle. The beneficial effect of this step is that it effectively summarizes the detailed differences within each group while maintaining the differences between groups. The final comprehensive color error value reflects both the overall color rendering capability and preserves the precision of group comparison.

[0145] In some implementations, such as Figure 5 As shown in step S45, the initial color error values ​​of the test color samples in each color sample group at the emission angle are statistically processed to calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle, including:

[0146] S451. Based on the initial color error value of the test color sample of each color sample group at the emission angle, perform aggregation calculation to obtain the group color error value of each color sample group at the emission angle.

[0147] Specifically, the initial color error values ​​of multiple test color samples within the same color attribute group are aggregated, for example, by taking the average, weighted average, median, or extreme values, to obtain the representative error index of that group at the current emission angle. Through aggregation, the differences between samples within a group can be transformed into a unified grouping result. The beneficial effect of this step is to reduce the impact of random fluctuations in individual samples on the overall result, improve the stability of the calculation, and preserve the differences between different color attribute groups.

[0148] S452. Based on the differences in importance of different color attribute groups in visual tasks, assign a grouping weight factor to the grouping color error value of each color sample group.

[0149] Specifically, weights are assigned to different color attribute groups based on their importance in human vision and practical application scenarios. For example, skin tone-related groups are given higher weight in color rendering evaluation, while low-saturation groups have lower weights in some applications. This weighting factor reflects the different contributions of different color groups to real-world visual tasks. The benefit of this step is increased flexibility and practicality, ensuring that the final index not only relies on mathematical averages but also reflects visual priorities in real-world applications.

[0150] S453. Based on the group color error value and group weight factor of each color sample group, calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle.

[0151] Specifically, the color error values ​​of each color sample group are multiplied by their corresponding group weights, and then weighted and synthesized to obtain the comprehensive color error value of the test light source at that emission angle. This comprehensive index can simultaneously consider the representative errors of different color groups and their importance in the visual task. The beneficial effect of this step is to form an angle-dependent error index that is more in line with the subjective evaluation of the human eye, providing a reliable basis for subsequent calculation of the color resolution index.

[0152] In some embodiments of this application, the light source color resolution evaluation method may also include, but is not limited to, the following steps:

[0153] S6. Obtain the associated reference light source based on the color temperature parameters of the test light source, and calculate the reference spectral power distribution of the reference light source within the preset wavelength range.

[0154] Specifically, color temperature is an important parameter for testing light sources, used to describe the perceived color of the light emitted by the light source. In the GB / T 7922 standard, color temperature is usually measured by correlated color temperature (CCT), with the unit being Kelvin (K). In some embodiments, the correlated color temperature (CCT) of the test light source can be calculated as a color temperature parameter according to the method described in GB / T 7922. The lower the color temperature parameter, the warmer the light; the higher the color temperature parameter, the cooler the light.

[0155] This step is used to select a reference object with standard optical characteristics for the test light source in order to objectively evaluate the color reproduction performance of the test light source. First, based on the color temperature parameters (in Kelvin) of the test light source, the system matches a standard reference light source with the closest color temperature in international lighting standards. For example, when the color temperature of the test light source is approximately 5000K, the system will select the CIE D50 daylight illuminator as the reference light source; if the color temperature is 2856K, then illuminator A may be selected as the comparison benchmark.

[0156] After selecting a reference light source, the system retrieves its spectral power distribution data as defined by the standard to obtain the optical power output curves of the reference light source at various wavelengths. This spectral distribution will serve as the basis for subsequent reference color sample analysis and performance evaluation.

[0157] In some embodiments, S6, obtaining the associated reference light source based on the color temperature parameters of the test light source, may also include, but is not limited to, the following steps:

[0158] S61. If the color temperature parameter is less than the first color temperature threshold, the obtained reference light source is a Planck illuminator.

[0159] Specifically, when evaluating the color of a test light source, to ensure the consistency and comparability of the evaluation results, a standard reference light source with a color temperature matching the test light source needs to be selected. The selection criteria for this reference light source are based on the color temperature parameters of the test light source and are combined with the technical specifications of the International Commission on Illumination (CIE) regarding the selection of reference light sources. Specifically, two color temperature thresholds are set: a first color temperature threshold and a second color temperature threshold, where the value of the second color temperature threshold is greater than the first color temperature threshold.

[0160] When the color temperature parameter of the test light source is less than the first color temperature threshold, the light source is judged to belong to the typical low color temperature range, such as a tungsten filament lamp or a warm-toned light source. In this case, the reference light source selected is the Planck illuminator. The Planck illuminator is an ideal blackbody radiation light source, and its spectral distribution can be directly derived from the color temperature using Planck's formula. It is widely used as a reference standard for low color temperature artificial light sources.

[0161] In some embodiments, the first color temperature threshold is set to 4000K. When the color temperature parameter T < 4000K, the obtained reference light source is a Planck illuminator, also known as a Planck radiator, which is an idealized light source based on Planck's radiation law. Planck's radiation law describes the spectral distribution of a blackbody (an object that can completely absorb incident radiation of any wavelength and has the maximum emissivity) at different temperatures.

[0162] S62. If the color temperature parameter is greater than the second color temperature threshold, the obtained reference light source is a daylight illuminator;

[0163] Specifically, when the color temperature parameter of the test light source is greater than the second color temperature threshold, the light source is determined to belong to the high color temperature range, such as daylight-type LEDs or natural light simulation lamps. In this case, the selected reference light source is a daylight illuminant. Daylight illuminants use the CIE-defined D-series standard daylight sources (such as D50 and D65) to simulate the spectral characteristics of natural sunlight at different color temperatures, suitable for evaluating light sources with a neutral to cool color tone. The second color temperature threshold is greater than the first color temperature threshold. Assuming the second color temperature threshold is set to 5000K, when the color temperature parameter T>5000K, the obtained reference light source is a daylight illuminant. A daylight illuminant is an illuminant with a relative spectral power distribution that is the same as or approximately the same as that of sunlight at a certain time, simulating natural sunlight.

[0164] S63. If the color temperature parameter is between the first color temperature threshold and the second color temperature threshold, the obtained reference light source is a mixture of Planck illuminator and daylight illuminator.

[0165] Specifically, if the color temperature parameter of the test light source is between the first and second color temperature thresholds, the system will consider the color temperature of the light source to be in the transition region between the Planck illuminator and the daylight illuminator. To avoid discontinuity errors caused by reference light source jumps in this critical region, the system will construct a hybrid reference light source. This hybrid is a composite light source obtained by weighting the spectral power distributions of the Planck illuminator and the daylight illuminator according to their color temperature ratios. Its mixing weight is usually determined by the relative position of the test light source's color temperature within the linear range. The hybrid reference light source retains the continuity at low color temperatures while gradually introducing high color temperature characteristics, achieving a smooth transition of the reference light source along the color temperature axis. When the color temperature parameter is between the first and second color temperature thresholds, i.e., 4000K <= T <= 5000K, the reference light source is a hybrid of the Planck illuminator and the daylight illuminator, and the corresponding reference spectral power distribution Sr is a preset linear combination of the Planck illuminator reference spectral power distribution (SrP) and the daylight illuminator reference spectral power distribution (SrD).

[0166] S7. Calculate the reference color resolution index of the reference light source based on the reference spectral power distribution and multiple test color samples;

[0167] Specifically, after obtaining the spectral power distribution of the reference light source, the system uses the same set of test color samples (usually multiple representative colors from a standard color swatch) to simulate their visual effects under reference light source illumination. The specific operations include: combining the spectral reflectance data of each test color sample with the reference spectral power distribution, applying the CIE color matching function to calculate its tristimulus values, and then performing steps such as color adaptation transformation, brightness correction, and hue angle calculation to finally obtain the color performance of these color samples under the reference light source. Next, these performance results are used to calculate the reference color resolution index. This index measures the ability of the reference light source to distinguish visual differences between different colors and is typically related to multiple factors such as hue error, neutral shift, and color spacing. The result serves as a reference benchmark for comparison with the performance of the test light source.

[0168] S8. Calculate the relative color resolution index of the test light source based on the reference color resolution index and the color resolution index.

[0169] Specifically, the difference in color resolution between the test light source and the reference light source is quantified, and a relative color resolution index is calculated. This index reflects the performance level of the test light source relative to the standard light source in terms of color performance by comparing the color resolution index of the test light source with the reference color resolution index of the reference light source.

[0170] The calculation method can use a normalized ratio, for example, taking the reference index as 100 and the test light source score as a proportion of that index. A correction factor can also be introduced to handle the effects of color temperature deviation. The closer the value is to 100 or the reference value, the closer the test light source is to the reference light source visually; a lower value indicates that the color resolution performance of the test light source is significantly weaker than the standard, which may lead to color perception distortion.

[0171] Understandably, depending on the usage scenario of the test light source and the comparison object, it is advisable to choose the relative color resolution index or color preference index in this application to evaluate the color rendering quality of the light source. Specifically, for cross-color temperature comparisons, an absolute index, i.e., the absolute color preference index, should be used. CDM For comparisons within the same color temperature, a relative index, namely the relative color preference index, should be used. .

[0172] Example 2

[0173] Please see Figure 6 Embodiment 2 of the present invention also provides a light source color resolution evaluation device, the device comprising:

[0174] The acquisition module is used to acquire the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles;

[0175] The tristimulus value module is used to calculate the tristimulus value and white point tristimulus value of each test color sample at the emission angle of the test light source, based on the bidirectional reflectance factor of multiple test color samples at the emission angle.

[0176] The calculation module is used to calculate the hue angle, lightness value and saturation value of each test color sample at the emission angle based on the tristimulus value and white point tristimulus value of each test color sample at the emission angle.

[0177] The error value module is used to obtain the comprehensive color error value of the test light source relative to the reference light source at the emission angle based on the hue angle, lightness value and saturation value of each test color sample at the emission angle.

[0178] The color resolution module is used to obtain the color resolution index of the test light source based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle.

[0179] The specific implementation of the light source color resolution evaluation device in this embodiment is basically the same as the specific implementation of the light source color resolution evaluation method described above, and will not be repeated here.

[0180] Example 3

[0181] In addition, combined Figure 1The light source color resolution evaluation method described in Embodiment 1 of the present invention can be implemented by an electronic device. Figure 7 A schematic diagram of the hardware structure of the electronic device provided in Embodiment 3 of the present invention is shown.

[0182] Electronic devices may include processors and memory storing computer program instructions.

[0183] Specifically, the processor may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement embodiments of the present invention.

[0184] The memory may include a large-capacity storage device for data or instructions. For example, and not limitingly, the memory may include a hard disk drive (HDD), a floppy disk drive, flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory may include removable or non-removable (or fixed) media. Where appropriate, the memory may be internal or external to a data processing device. In a particular embodiment, the memory is a non-volatile solid-state memory. In a particular embodiment, the memory includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0185] The processor reads and executes computer program instructions stored in the memory to implement any of the light source color resolution evaluation methods in the above embodiments.

[0186] In one example, the electronic device may also include a communication interface and a bus. For example, Figure 7 As shown, the processor 701, memory 702, and communication interface 703 are connected through bus 710 and complete communication with each other.

[0187] The communication interface is mainly used to enable communication between various modules, devices, units and / or equipment in the embodiments of the present invention.

[0188] A bus, including hardware, software, or both, couples components of the device together. For example, and not limitingly, a bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, a bus may include one or more buses. While specific buses are described and illustrated in embodiments of the invention, the invention contemplates any suitable bus or interconnect.

[0189] Example 4

[0190] In addition, in conjunction with the light source color resolution evaluation method in Embodiment 1 above, Embodiment 4 of the present invention can also provide a computer-readable storage medium for implementation. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the light source color resolution evaluation methods in the above embodiments.

[0191] In summary, the embodiments of the present invention provide a method, apparatus, device, and storage medium for evaluating the color resolution of a light source.

[0192] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0193] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the required tasks. The programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0194] It should also be noted that the exemplary embodiments mentioned in this invention describe methods or systems based on a series of steps or apparatus. However, this invention is not limited to the order of the steps described above; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0195] The above description is merely a specific embodiment of the present invention. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the protection scope of the present invention.

Claims

1. A method for evaluating the color resolution of a light source, characterized in that, The method includes: Based on the output power of the test light source, obtain the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles; For each exit angle, based on the bidirectional reflectance factor of multiple test color samples at the exit angle, calculate the tristimulus value and white point tristimulus value of each test color sample at the exit angle of the test light source; Based on the tristimulus values ​​and white point tristimulus values ​​of each test color sample at the specified exit angle, calculate the hue angle, lightness value, and saturation value of each test color sample at the specified exit angle. Based on the hue angle, lightness value, and saturation value of each test color sample at the emission angle, the comprehensive color error value of the test light source relative to the reference light source at the emission angle is obtained. The color resolution index of the test light source is obtained based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle.

2. The light source color resolution evaluation method according to claim 1, characterized in that, For each emission angle, based on the bidirectional reflectance factor of multiple test color samples at that emission angle, the tristimulus value and white point tristimulus value of each test color sample at the emission angle of the test light source are calculated, including: For each emission angle, the bidirectional reflectance factor of multiple test color samples was obtained; Based on the CIE color matching function, the bidirectional reflectance factor, the preset wavelength range, and the spectral power distribution, calculate the tristimulus values ​​of each test color sample under the test light source; Based on the CIE color matching function, the preset wavelength range, and the spectral power distribution, the white point tristimulus value of the light source under the test light source is calculated.

3. The light source color resolution evaluation method according to claim 1, characterized in that, The calculation of the hue angle, lightness value, and saturation value of each test color sample at the specified emission angle, based on the tristimulus value and white point tristimulus value of each test color sample at the specified emission angle, includes: For each test color sample, the input pairing required for color adaptation conversion is performed based on the tristimulus value of the test color sample and the corresponding white point tristimulus value, resulting in the input pair for color adaptation conversion; The cone response value is obtained by color adaptation conversion of the tristimulus values ​​of the test color sample based on the white point tristimulus values. Based on the environment or observation settings, the visual cone response value is subjected to brightness adaptation conversion and nonlinear response compression processing to obtain the visual cone reference value; Calculate the first color channel value and the second color channel value based on the aforementioned cone reference value; Calculate the hue angle based on the first color channel value and the second color channel value; The luminance channel value corresponding to the aforementioned cone reference value is used as the luminance value; The saturation value is calculated based on the Euclidean modulus of the first and second color channel values.

4. The light source color resolution evaluation method according to claim 1, characterized in that, The step of obtaining the comprehensive color error value of the test light source relative to the reference light source at the emission angle based on the hue angle, lightness value, and saturation value of each test color sample at the emission angle includes: The multiple test color samples are classified according to their color attributes to form multiple color sample groups; For each color sample group, calculate the error values ​​relative to the reference light source in each dimension of hue angle, lightness value and saturation value of the test color sample in the color sample group at the emission angle. Based on the sensitivity of the human eye to changes in different color attributes, corresponding perceptual weighting factors are assigned to the error values ​​of each dimension under the emission angle. The error values ​​of each dimension of the test color sample in the color sample group at the emission angle are weighted and combined with their perception weighting factors to obtain the initial color error value of the test color sample in the color sample group at the emission angle. The initial color error values ​​of the test color samples in each color sample group at the emission angle are statistically processed to calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle.

5. The light source color resolution evaluation method according to claim 4, characterized in that, The initial color error values ​​of the test color samples in each color sample group at the emission angle are statistically processed to calculate the comprehensive color error value of the test light source relative to the reference light source at the emission angle, including: Based on the initial color error value of the test color sample of each color sample group at the emission angle, an aggregation operation is performed to obtain the group color error value of each color sample group at the emission angle. Based on the differences in importance of different color attribute groups in visual tasks, a grouping weight factor is assigned to the grouping color error value of each color sample group. Based on the group color error value and group weight factor of each color sample group, the comprehensive color error value of the test light source relative to the reference light source at the emission angle is calculated.

6. The light source color resolution evaluation method according to any one of claims 1-5, characterized in that, The method further includes: Based on the color temperature parameters of the test light source, an associated reference light source is obtained, and the reference spectral power distribution of the reference light source within the preset wavelength range is calculated. The reference color resolution index of the reference light source is calculated based on the reference spectral power distribution and multiple test color samples; The relative color resolution index of the test light source is calculated based on the reference color resolution index and the color resolution index.

7. The light source color resolution evaluation method according to claim 6, characterized in that, The step of obtaining the associated reference light source based on the color temperature parameters of the test light source includes: If the color temperature parameter is less than the first color temperature threshold, the obtained reference light source is a Planck illuminator; If the color temperature parameter is greater than the second color temperature threshold, the obtained reference light source is a daylight illuminator; wherein, the second color temperature threshold is greater than the first color temperature threshold; If the color temperature parameter is between the first color temperature threshold and the second color temperature threshold, the obtained reference light source is a mixture of the Planck illuminator and the daylight illuminator.

8. A light source color resolution evaluation device, characterized in that, The device includes: The acquisition module is used to acquire the spectral power distribution of the test light source within a preset wavelength range at multiple emission angles; The tristimulus value module is used to calculate the tristimulus value and white point tristimulus value of each test color sample at the emission angle of the test light source, based on the bidirectional reflectance factor of multiple test color samples at the emission angle. The calculation module is used to calculate the hue angle, lightness value and saturation value of each test color sample at the emission angle based on the tristimulus value and white point tristimulus value of each test color sample at the emission angle. The error value module is used to obtain the comprehensive color error value of the test light source relative to the reference light source at the emission angle based on the hue angle, lightness value and saturation value of each test color sample at the emission angle. The color resolution module is used to obtain the color resolution index of the test light source based on the neutrality index of the test light source and the comprehensive color error value corresponding to each emission angle.

9. An electronic device, characterized in that, include: At least one processor, at least one memory, and computer program instructions stored in the memory, which, when executed by the processor, implement the method as described in any one of claims 1-7.

10. A storage medium storing computer program instructions thereon, characterized in that, The method as described in any one of claims 1-7 is implemented when the computer program instructions are executed by the processor.

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